|
Makerere University Research Repository >
Faculty of Computing and Information Technology >
Theses & Dissertations (CIT) >
Please use this identifier to cite or link to this item:
http://hdl.handle.net/123456789/598
|
| Title: | Hidden Markov modelling for analysing significant nucleotide regions in DNA polymerised genes: a case study of the Malaria Plasmodium Genome |
| Authors: | Murangira, B. Jones |
| Keywords: | Markov modelling
Nucleotide
DNA polymerised genes |
| Issue Date: | Oct-2008 |
| Abstract: | Nucleotide duplication is one process that enables DNA to flexibly adapt and evolve in a changing environment. Duplication creates highly significant (non-tandem) and low significant (tandem) sequential regions that over time may mutate to form unique regions [1, 2]. DNA regional sequences
are of interest biologically in the context of their role in evolution and association to human diseases [3, 4, 5]. This research project therefore, focused on analysing tandem and non-tandem nucleotide regions in DNA polymerised genes. The project designed a forward-backward algorithm based on Hidden Markov Models (HMMs), and consequently implemented a system for analysing respective tandem and non-tandem nucleotide variations (regions) in a polymerised genome for one of the worst killer diseases; malaria. The results of the general system implemented on matlab, were then tested on posterior probability threshold scores on a graphical output. |
| Description: | A Project report submitted to School of Graduate Studies in partial fulfillment for the award of Master of Science in
Computer Science Degree of Makerere University. |
| URI: | http://hdl.handle.net/123456789/598 |
| Appears in Collections: | Theses & Dissertations (CIT)
|
Files in This Item:
| File |
Description |
Size | Format |
|---|
| murangira-jones-cit-masters-report.pdf | Thesis report | 246Kb | Adobe PDF | View/Open |
|
All items in DSpace are protected by copyright, with all rights reserved.
|
